Neurological profiles for market matching and stimulus presentation

ABSTRACT

A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

TECHNICAL FIELD

The present disclosure relates to neurological profiles. More particularly, the present disclosure relates to determining neurological profiles for market matching and stimulus presentation.

DESCRIPTION OF RELATED ART

A variety of conventional systems are available for presenting advertising to a user. In some instances, advertising can be personalized based on demographic information. For example, a web site may identify a user's gender and present product matches directed to that gender. A program having a predominantly wealthier audience may include advertising directed at wealthier individuals. Viewers in a particular local market may be presented with commercials tailored to that local market.

Although a variety of advertising presentation mechanisms are available, the ability to tailor results to a particular user or group are limited. Consequently, it is desirable to provide improved mechanisms for performing market matching and stimulus presentation.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may best be understood by reference to the following description taken in conjunction with the accompanying drawings, which illustrate particular example embodiments.

FIG. 1 illustrates one example of a system for performing market matching and stimulus presentation.

FIG. 2 illustrates one example of a neurological profile associated with determining introversion/extroversion.

FIG. 3 illustrates one example of a neurological profile associated with determining visual element limitations.

FIG. 4 illustrates one example of neuro-response data associated with evaluating simultaneous visual element processing.

FIG. 5 illustrates one example of a system for analyzing a categorical perception shift boundary and implementing neurologically informed morphing.

FIG. 6 illustrates one example of a technique for performing market matching and stimulus presentation using a neurological profile.

FIG. 7 provides one example of a system that can be used to implement one or more mechanisms.

DESCRIPTION OF PARTICULAR EMBODIMENTS

Reference will now be made in detail to some specific examples of the invention including the best modes contemplated by the inventors for carrying out the invention. Examples of these specific embodiments are illustrated in the accompanying drawings. While the invention is described in conjunction with these specific embodiments, it will be understood that it is not intended to limit the invention to the described embodiments. On the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the invention as defined by the appended claims.

For example, the techniques and mechanisms of the present invention will be described in the context of particular types of media. However, it should be noted that the techniques and mechanisms of the present invention apply to a variety of different types of media. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. Particular example embodiments of the present invention may be implemented without some or all of these specific details. In other instances, well known process operations have not been described in detail in order not to unnecessarily obscure the present invention.

Various techniques and mechanisms of the present invention will sometimes be described in singular form for clarity. However, it should be noted that some embodiments include multiple iterations of a technique or multiple instantiations of a mechanism unless noted otherwise. For example, a system uses a processor in a variety of contexts. However, it will be appreciated that a system can use multiple processors while remaining within the scope of the present invention unless otherwise noted. Furthermore, the techniques and mechanisms of the present invention will sometimes describe a connection between two entities. It should be noted that a connection between two entities does not necessarily mean a direct, unimpeded connection, as a variety of other entities may reside between the two entities. For example, a processor may be connected to memory, but it will be appreciated that a variety of bridges and controllers may reside between the processor and memory. Consequently, a connection does not necessarily mean a direct, unimpeded connection unless otherwise noted.

Overview

A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

Example Embodiments

A variety of mechanisms for matching particular demographic characteristics associated with a user with particular products, services, and people are available. In one example, a web site recognizes that an individual lives in a particular city and provides services messages associated with that city. In another example, a retailer knows a buyer's purchasing patterns and sends marketing materials tailored to those purchasing patterns. In still another example, a networking site determines a user's interests and makes matches based on those interests.

Providing market matching and stimulus presentation services based on demographic characteristics is effective but limited. Some characteristics associated with a user or buyer may not be easily discernible. In many instances, subjects may not even be aware of their own preferences, capabilities, and behaviors. The techniques and mechanisms of the present invention recognize that cognitive, social, and emotional behavior is influenced by social, environmental, and genetic factors reflected in neurological profiles.

According to various embodiments, neurological profiles associated with users are determined to better perform market matching and stimulus presentation. In particular embodiments, introversion/extroversion levels associated with a user are determined in order to tailor advertising to the user. For example, an extroverted user is presented with an image showing a large group of people while an introverted user is presented with an image showing one or two people. Advertising tailored to particular introversion/extroversion levels may be selected and tailored to the user. The techniques and mechanisms of the present invention recognize that introverted users may be uncomfortable when provided with materials showing large groups. Introversion/extroversion levels may be provided by a user, determined based on user activity, ascertained using social, environmental, and/or genetic factors, or determined using neuro-response data.

According to various embodiments, neurological profiles are generated for users and the neurological profiles are matched with cognitive, social, demographic, and behavioral measures of marketing response. In particular embodiments, extroverted individuals may respond positively to party invitations while introverted individuals may respond positively to book signings. Marketing categories or stimulus materials can be associated with particular neurological profiles or templates.

In another example, the number of visual elements a user can simultaneously process is determined. According to various embodiments, it is recognized that some individuals can simultaneously process three visual elements while others can process five visual elements. In particular embodiments, the three visual elements may be three portions of a webpage. The number of visual elements simultaneously processed can decrease with age. According to various embodiments, the number of simultaneous visual elements can be automatically selected based on demographic information, user selection, social, environmental, and/or genetic factors, and/or neuro-response data.

According to various embodiments, neurological profiles will show increased neuro-response activity up to the maximum number of visual elements a user can process. Advertising, websites, and other stimulus can be tailored to particular individuals based on visual element processing capabilities.

In still other examples, the amount of detail a user is drawn do is determined using neurological profiles. According to various embodiments, it is recognized that particular populations, groups, and subgroups of people are drawn to detail while others generally disregard detail. The amount of detail includes intricacies in the design of a product. According to various embodiments, marketing categories presented to a user can be automatically selected based on demographic information, user selection, social, environmental, and/or genetic factors, and/or neuro-response data.

Although particular neurological profile characteristics are described, it should be noted that a wide variety of characteristics may be evaluated using neurological profiles. According to various embodiments, the amount of dynamism needed in media to elicit a response may be determined using neurological profiles. In particular embodiments, younger individuals growing up in a more media immersed environment may require more constantly dynamism and changing visual elements in order to hold attention. The number of distracters, number of repetitions, or the length of a message may also be varied based on neurological profiles.

The targeted premium placements and advertisement spots can be presented to a user on social networking sites, job placements sites, program commercials, or other media.

FIG. 1 illustrates one example of a system for generating neurological profiles for market matching and stimulus presentation. According to various embodiments, a neurological profile generator 111 receives user information. In particular embodiments, the user information includes user input data 101, user activity 103, social, genetic, and environmental factors 105, and neuro-response data 107. The user input data 101 may be forms or surveys completed by a user. User activity 103 may include user media consumption patterns and purchasing patterns. For example, user activity 103 may indicate that a user prefers highly adorned and detail oriented web content. Social, genetic, and environmental factors 105 may include profiles of friends and family members, cultural and genetic differences, etc.

According to various embodiments, users in a particular country may more likely be introverted than users in other countries. In another example, an individual subscribing to a particular religion may more likely prefer certain types of activities. In particular embodiments, neuro-response data 107 may also be obtained. Neuro-response data 107 may be obtained from the user individually or deduced from other data. Neuro-response data 107 may include user responses collected using Electroencephalography (EEG) or function Magnetic Resonance Imaging (fMRI) when exposed to particular stimulus material such as video showing large groups of people or highly ornate print advertisements.

In particular embodiments, the neurological profile generator 111 receives and user information and generate neurological profiles of users, user subgroups, and user groups. According to various embodiments, the neurological profiles identify introversion/extroversion levels 121, simultaneous visual element processing capability 123, detail processing levels 125, etc. The neurological profile generator 111 may determine that a particular user is introverted, can processing 3 visual elements simultaneously, and does not have an eye for detail. Although on particular types of neurological profile information are described, it should be noted that other neurological profile characteristics can also be determined. For example, levels of optimism/pessimism, thinking/feeling, judging/perceiving, and sensing/intuition can be identified using a neurological profile generator 111. The neurological profile information is passed to a stimulus selection device 131.

According to various embodiments, the stimulus selection device 131 matches neurological profile information to cognitive, social, demographic, and behavioral measures of marketing response. Marketing categories and materials can be matched to particular neurological profiles. In particular embodiments, a template database 133 is accessed to perform matching. The stimulus selection device may indicate that certain types or versions of advertisements are more appropriate for a user with a particular neurological profile.

According to various embodiments, the market matching stimulus selection device 131 provides selection information to entities such as service/content providers 143, media databases 141, and media devices 145. Programming, social network sites, shopping destinations, can place targeted premium placements and advertisement spots 151 as well as provide targeted products and services.

FIG. 2 illustrates one example of obtaining a neurological profile associated with introversion/extroversion. According to various embodiments, user input is received at 201. User input may include user submitted forms, surveys, and evaluations. At 205, user activity is analyzed. User activity may include purchasing patterns, activity patterns, etc. Although user input and user activity is described, it should be noted that in various embodiments, user input and user activity may not be used or available. According to various embodiments, social, cultural, and genetic factors are analyzed at 207. Social, cultural, and genetic factors can have significant correlations with user extroversion and introversion levels. In particular embodiments, subjects growing up exposed to a particular culture may tend to be much more introverted than subjects growing up exposed to another culture. It should be noted that other factors such as developmental or neo-natal factors can be evaluated as well.

According to various embodiments, subjects are exposed to extrovert oriented and introvert oriented stimulus at 209. Extrovert oriented stimulus may include video scenes of a large group gathering or social event. Introvert oriented stimulus may include video scenes of reading or relaxing alone. Subjects may also be exposed to stimulus material in group and individual settings at 211 to further gauge introversion/extroversion levels. At 213, neuro-response data is receive and analyzed to determine subject neuro-response activity when exposed to extrovert oriented stimulus and introvert oriented stimulus in group and individual settings. Responses may be compared to responses of known introverts and extroverts and/or analyzed to determine attention, emotional engagement, and memory retention levels in response to the stimulus.

FIG. 3 illustrates one example of determining a neurological profile associated with simultaneous visual element processing capabilities. According to various embodiments, user input is received at 301. User input may include user submitted forms, surveys, and evaluations. At 305, user activity is analyzed. User activity may include purchasing patterns, activity patterns, etc. Although user input and user activity is described, it should be noted that in various embodiments, user input and user activity may not be used or available. According to various embodiments, social, cultural, and genetic factors are analyzed at 307. Social, cultural, and genetic factors can have significant correlations with visual element processing capabilities. In particular embodiments, younger subjects tend to be able to process approximately four or five simultaneous visual elements. The visual elements may be different portions of a web page or different aspects of an image. In particular embodiments, older subjects tend to be able to processing approximately three or four simultaneous visual elements and may be more easily distracted.

According to various embodiments, subjects are exposed to stimulus having varying numbers of simultaneous visual elements at 309. Neuro-response data such as EEG, fMRI, MEG, and Electrooculography (EOG) data is received at 311. Neuro-response data may be measured and analyzed on an individual basis, or on a subgroup and group basis.

FIG. 4 illustrates one example of response data associated with exposing a subject to simultaneous visual elements. Neuro-response significance 401 is mapped as a function of time 403. According to various embodiments, response 407 corresponds to an EEG response for a subject exposed to one visual element. Response 409 may correspond to an EEG response for a subject exposed to two visual elements. Response 411 may correspond to an EEG response for a subject exposed to three visual elements.

According to various embodiments, a younger subject may exhibit EEG responses corresponding to responses 415 and 417 when exposed to four or five simultaneous visual elements respectively. However, other subjects may exhibit EEG responses corresponding to response 411 when exposed to three, four, or five simultaneous visual elements. No additional neural activity may be measured as elements are added to an image. According to various embodiments, an older subject may show response 411 for a number of simultaneous visual elements greater than or equal to three. In particular embodiments, a younger subject may show response 417 for a number of simultaneous visual elements greater than or equal to five.

FIG. 5 illustrates one example of a system for evaluating neurological profiles. Neuro-response data can be collected and analyzed to determine neurological profile characteristics such as introversion/extroversion, simultaneous visual elements processing capability, attention span, etc. Neuro-response data can also be used to select media appropriate to the neurological profile characteristics of a viewer for presentation to the viewer.

According to various embodiments, a system for evaluating neurological profiles includes a stimulus presentation device 501. In particular embodiments, the stimulus presentation device 501 is merely a display, monitor, screen, speaker, etc., that provides stimulus material to a user. Continuous and discrete modes are supported. According to various embodiments, the stimulus presentation device 501 also has protocol generation capability to allow intelligent customization of stimuli provided to multiple subjects in different markets.

According to various embodiments, stimulus presentation device 501 could include devices such as televisions, cable consoles, computers and monitors, projection systems, display devices, speakers, tactile surfaces, etc., for presenting the video and audio from different networks, local networks, cable channels, syndicated sources, websites, internet content aggregators, portals, service providers, etc.

According to various embodiments, the subjects 503 are connected to data collection devices 505. The data collection devices 505 may include a variety of neuro-response measurement mechanisms including neurological and neurophysiological measurements systems. According to various embodiments, neuro-response data includes central nervous system, autonomic nervous system, and effector data.

Some examples of central nervous system measurement mechanisms include Functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG), optical imaging, and Electroencephalography (EEG). fMRI measures blood oxygenation in the brain that correlates with increased neural activity. However, current implementations of fMRI have poor temporal resolution of few seconds. MEG measures the magnetic fields produced by electrical activity in the brain via extremely sensitive devices such as superconducting quantum interference devices (SQUIDs). optical imaging measures deflection of light from a laser or infrared source to determine anatomic or chemical properties of a material. EEG measures electrical activity associated with post synaptic currents occurring in the milliseconds range. Subcranial EEG can measure electrical activity with the most accuracy, as the bone and dermal layers weaken transmission of a wide range of frequencies. Nonetheless, surface EEG provides a wealth of electrophysiological information if analyzed properly.

Autonomic nervous system measurement mechanisms include Galvanic Skin Response (GSR), Electrocardiograms (EKG), pupillary dilation, etc. Effector measurement mechanisms include Electrooculography (EOG), eye tracking, facial emotion encoding, reaction time etc.

According to various embodiments, the techniques and mechanisms of the present invention intelligently blend multiple modes and manifestations of precognitive neural signatures with cognitive neural signatures and post cognitive neurophysiological manifestations to more accurately allow assessment of alternate media. In some examples, autonomic nervous system measures are themselves used to validate central nervous system measures. Effector and behavior responses are blended and combined with other measures. According to various embodiments, central nervous system, autonomic nervous system, and effector system measurements are aggregated into a measurement that allows definitive evaluation stimulus material

In particular embodiments, the data collection devices 505 include EEG 511, EOG 513, and fMRI 515. In some instances, only a single data collection device is used. Data collection may proceed with or without human supervision.

The data collection device 505 collects neuro-response data from multiple sources. This includes a combination of devices such as central nervous system sources (EEG, MEG, fMRI, optical imaging), autonomic nervous system sources (EKG, pupillary dilation), and effector sources (EOG, eye tracking, facial emotion encoding, reaction time). In particular embodiments, data collected is digitally sampled and stored for later analysis. In particular embodiments, the data collected could be analyzed in real-time. According to particular embodiments, the digital sampling rates are adaptively chosen based on the neurophysiological and neurological data being measured.

In one particular embodiment, the system includes EEG 511 measurements made using scalp level electrodes, EOG 513 measurements made using shielded electrodes to track eye data, functional Magnetic Resonance Imaging (fMRI) 515 measurements made non-invasively to show haemodynamic response related to neural activity, using a differential measurement system, a facial muscular measurement through shielded electrodes placed at specific locations on the face, and a facial affect graphic and video analyzer adaptively derived for each individual.

In particular embodiments, the data collection devices are clock synchronized with a stimulus presentation device 501. In particular embodiments, the data collection devices 505 also include a condition evaluation subsystem that provides auto triggers, alerts and status monitoring and visualization components that continuously monitor the status of the subject, data being collected, and the data collection instruments. The condition evaluation subsystem may also present visual alerts and automatically trigger remedial actions. According to various embodiments, the data collection devices include mechanisms for not only monitoring subject neuro-response to stimulus materials, but also include mechanisms for identifying and monitoring the stimulus materials. For example, data collection devices 505 may be synchronized with a set-top box to monitor channel changes. In other examples, data collection devices 505 may be directionally synchronized to monitor when a subject is no longer paying attention to stimulus material. In still other examples, the data collection devices 505 may receive and store stimulus material generally being viewed by the subject, whether the stimulus is a program, a commercial, printed material, or a scene outside a window. The data collected allows analysis of neuro-response information and correlation of the information to actual stimulus material and not mere subject distractions.

According to various embodiments, the system also includes a data cleanser and analyzer device 521. In particular embodiments, the data cleanser and analyzer device 521 filters the collected data to remove noise, artifacts, and other irrelevant data using fixed and adaptive filtering, weighted averaging, advanced component extraction (like PCA, ICA), vector and component separation methods, etc. This device cleanses the data by removing both exogenous noise (where the source is outside the physiology of the subject, e.g. a phone ringing while a subject is viewing a video) and endogenous artifacts (where the source could be neurophysiological, e.g. muscle movements, eye blinks, etc.).

The artifact removal subsystem includes mechanisms to selectively isolate and review the response data and identify epochs with time domain and/or frequency domain attributes that correspond to artifacts such as line frequency, eye blinks, and muscle movements. The artifact removal subsystem then cleanses the artifacts by either omitting these epochs, or by replacing these epoch data with an estimate based on the other clean data (for example, an EEG nearest neighbor weighted averaging approach).

According to various embodiments, the data cleanser and analyzer device 521 is implemented using hardware, firmware, and/or software.

The data analyzer portion uses a variety of mechanisms to analyze underlying data in the system to determine resonance. According to various embodiments, the data analyzer customizes and extracts the independent neurological and neuro-physiological parameters for each individual in each modality, and blends the estimates within a modality as well as across modalities to elicit an enhanced response to the presented stimulus material. In particular embodiments, the data analyzer aggregates the response measures across subjects in a dataset.

According to various embodiments, neurological and neuro-physiological signatures are measured using time domain analyses and frequency domain analyses. Such analyses use parameters that are common across individuals as well as parameters that are unique to each individual. The analyses could also include statistical parameter extraction and fuzzy logic based attribute estimation from both the time and frequency components of the synthesized response.

In some examples, statistical parameters used in a blended effectiveness estimate include evaluations of skew, peaks, first and second moments, distribution, as well as fuzzy estimates of attention, emotional engagement and memory retention responses.

According to various embodiments, the data analyzer may include an intra-modality response synthesizer and a cross-modality response synthesizer. In particular embodiments, the intra-modality response synthesizer is configured to customize and extract the independent neurological and neurophysiological parameters for each individual in each modality and blend the estimates within a modality analytically to elicit an enhanced response to the presented stimuli. In particular embodiments, the intra-modality response synthesizer also aggregates data from different subjects in a dataset.

According to various embodiments, the cross-modality response synthesizer or fusion device blends different intra-modality responses, including raw signals and signals output. The combination of signals enhances the measures of effectiveness within a modality. The cross-modality response fusion device can also aggregate data from different subjects in a dataset.

According to various embodiments, the data analyzer also includes a composite enhanced effectiveness estimator (CEEE) that combines the enhanced responses and estimates from each modality to provide a blended estimate of the effectiveness. In particular embodiments, blended estimates are provided for each exposure of a subject to stimulus materials. The blended estimates are evaluated over time to assess resonance characteristics. According to various embodiments, numerical values are assigned to each blended estimate. The numerical values may correspond to the intensity of neuro-response measurements, the significance of peaks, the change between peaks, etc. Higher numerical values may correspond to higher significance in neuro-response intensity. Lower numerical values may correspond to lower significance or even insignificant neuro-response activity. In other examples, multiple values are assigned to each blended estimate. In still other examples, blended estimates of neuro-response significance are graphically represented to show changes after repeated exposure.

According to various embodiments, a data analyzer passes data to a resonance estimator that assesses and extracts resonance patterns. In particular embodiments, the resonance estimator determines entity positions in various stimulus segments and matches position information with eye tracking paths while correlating saccades with neural assessments of attention, memory retention, and emotional engagement. In particular embodiments, the resonance estimator stores data in the priming repository system. As with a variety of the components in the system, various repositories can be co-located with the rest of the system and the user, or could be implemented in remote locations.

FIG. 6 illustrates an example of a technique for analyzing neurological profiles. At 601, a neurological profile for a user, user subgroup, and/or a user group is determined. According to various embodiments, the neurological profile may be determined using user input data, user activity, social, genetic, and environmental factors, and neuro-response data. In particular embodiments, the neurological profile may also be derived based on demographic factors associated with the user. According to various embodiments, templates corresponding to the neurological profile are identified at 605. Templates may be identified by finding corresponding EEG and fMRI response data. Templates may be associated with introverts, extroverts, detail oriented individuals, individuals capable of processing numerous simultaneous visual elements, etc.

According to various embodiments, the templates may be generated using neuro-response data. For example, subjects known to be introverts through a variety of measurements may have neuro-response measurements collected and aggregated to create one or more introvert templates.

According to various embodiments, data analysis is performed. Data analysis may include intra-modality response synthesis and cross-modality response synthesis to enhance effectiveness measures. It should be noted that in some particular instances, one type of synthesis may be performed without performing other types of synthesis. For example, cross-modality response synthesis may be performed with or without intra-modality synthesis.

A variety of mechanisms can be used to perform data analysis. In particular embodiments, a stimulus attributes repository is accessed to obtain attributes and characteristics of the stimulus materials, along with purposes, intents, objectives, etc. In particular embodiments, EEG response data is synthesized to provide an enhanced assessment of effectiveness. According to various embodiments, EEG measures electrical activity resulting from thousands of simultaneous neural processes associated with different portions of the brain. EEG data can be classified in various bands. According to various embodiments, brainwave frequencies include delta, theta, alpha, beta, and gamma frequency ranges. Delta waves are classified as those less than 4 Hz and are prominent during deep sleep. Theta waves have frequencies between 3.5 to 7.5 Hz and are associated with memories, attention, emotions, and sensations. Theta waves are typically prominent during states of internal focus.

Alpha frequencies reside between 7.5 and 13 Hz and typically peak around 10 Hz. Alpha waves are prominent during states of relaxation. Beta waves have a frequency range between 14 and 30 Hz. Beta waves are prominent during states of motor control, long range synchronization between brain areas, analytical problem solving, judgment, and decision making. Gamma waves occur between 30 and 60 Hz and are involved in binding of different populations of neurons together into a network for the purpose of carrying out a certain cognitive or motor function, as well as in attention and memory. Because the skull and dermal layers attenuate waves in this frequency range, brain waves above 75-80 Hz are difficult to detect and are often not used for stimuli response assessment.

However, the techniques and mechanisms of the present invention recognize that analyzing high gamma band (kappa-band: Above 60 Hz) measurements, in addition to theta, alpha, beta, and low gamma band measurements, enhances neurological attention, emotional engagement and retention component estimates. In particular embodiments, EEG measurements including difficult to detect high gamma or kappa band measurements are obtained, enhanced, and evaluated. Subject and task specific signature sub-bands in the theta, alpha, beta, gamma and kappa bands are identified to provide enhanced response estimates. According to various embodiments, high gamma waves (kappa-band) above 80 Hz (typically detectable with sub-cranial EEG and/or magnetoencephalograophy) can be used in inverse model-based enhancement of the frequency responses to the stimuli.

Various embodiments of the present invention recognize that particular sub-bands within each frequency range have particular prominence during certain activities. A subset of the frequencies in a particular band is referred to herein as a sub-band. For example, a sub-band may include the 40-45 Hz range within the gamma band. In particular embodiments, multiple sub-bands within the different bands are selected while remaining frequencies are band pass filtered. In particular embodiments, multiple sub-band responses may be enhanced, while the remaining frequency responses may be attenuated.

An information theory based band-weighting model is used for adaptive extraction of selective dataset specific, subject specific, task specific bands to enhance the effectiveness measure. Adaptive extraction may be performed using fuzzy scaling. Stimuli can be presented and enhanced measurements determined multiple times to determine the variation profiles across multiple presentations. Determining various profiles provides an enhanced assessment of the primary responses as well as the longevity (wear-out) of the marketing and entertainment stimuli. The synchronous response of multiple individuals to stimuli presented in concert is measured to determine an enhanced across subject synchrony measure of effectiveness. According to various embodiments, the synchronous response may be determined for multiple subjects residing in separate locations or for multiple subjects residing in the same location.

Although a variety of synthesis mechanisms are described, it should be recognized that any number of mechanisms can be applied—in sequence or in parallel with or without interaction between the mechanisms.

Although intra-modality synthesis mechanisms provide enhanced significance data, additional cross-modality synthesis mechanisms can also be applied. A variety of mechanisms such as EEG, Eye Tracking, fMRI, EOG, and facial emotion encoding are connected to a cross-modality synthesis mechanism. Other mechanisms as well as variations and enhancements on existing mechanisms may also be included. According to various embodiments, data from a specific modality can be enhanced using data from one or more other modalities. In particular embodiments, EEG typically makes frequency measurements in different bands like alpha, beta and gamma to provide estimates of significance. However, the techniques of the present invention recognize that significance measures can be enhanced further using information from other modalities.

For example, facial emotion encoding measures can be used to enhance the valence of the EEG emotional engagement measure. EOG and eye tracking saccadic measures of object entities can be used to enhance the EEG estimates of significance including but not limited to attention, emotional engagement, and memory retention. According to various embodiments, a cross-modality synthesis mechanism performs time and phase shifting of data to allow data from different modalities to align. In some examples, it is recognized that an EEG response will often occur hundreds of milliseconds before a facial emotion measurement changes. Correlations can be drawn and time and phase shifts made on an individual as well as a group basis. In other examples, saccadic eye movements may be determined as occurring before and after particular EEG responses. According to various embodiments, fMRI measures are used to scale and enhance the EEG estimates of significance including attention, emotional engagement and memory retention measures.

Evidence of the occurrence or non-occurrence of specific time domain difference event-related potential components (like the DERP) in specific regions correlates with subject responsiveness to specific stimulus. According to various embodiments, ERP measures are enhanced using EEG time-frequency measures (ERPSP) in response to the presentation of the marketing and entertainment stimuli. Specific portions are extracted and isolated to identify ERP, DERP and ERPSP analyses to perform. In particular embodiments, an EEG frequency estimation of attention, emotion and memory retention (ERPSP) is used as a co-factor in enhancing the ERP, DERP and time-domain response analysis.

EOG measures saccades to determine the presence of attention to specific objects of stimulus. Eye tracking measures the subject's gaze path, location and dwell on specific objects of stimulus. According to various embodiments, EOG and eye tracking is enhanced by measuring the presence of lambda waves (a neurophysiological index of saccade effectiveness) in the ongoing EEG in the occipital and extra striate regions, triggered by the slope of saccade-onset to estimate the significance of the EOG and eye tracking measures. In particular embodiments, specific EEG signatures of activity such as slow potential shifts and measures of coherence in time-frequency responses at the Frontal Eye Field (FEF) regions that preceded saccade-onset are measured to enhance the effectiveness of the saccadic activity data.

According to various embodiments, facial emotion encoding uses templates generated by measuring facial muscle positions and movements of individuals expressing various emotions prior to the testing session. These individual specific facial emotion encoding templates are matched with the individual responses to identify subject emotional response. In particular embodiments, these facial emotion encoding measurements are enhanced by evaluating inter-hemispherical asymmetries in EEG responses in specific frequency bands and measuring frequency band interactions. The techniques of the present invention recognize that not only are particular frequency bands significant in EEG responses, but particular frequency bands used for communication between particular areas of the brain are significant. Consequently, these EEG responses enhance the EMG, graphic and video based facial emotion identification.

According to various embodiments, post-stimulus versus pre-stimulus differential measurements of ERP time domain components in multiple regions of the brain (DERP) are measured. The differential measures give a mechanism for eliciting responses attributable to the stimulus. For example the messaging response attributable to an advertisement or the brand response attributable to multiple brands is determined using pre-resonance and post-resonance estimates

Market categories associated with the templates are selected for the user at 607. In particular embodiments, stimulus material associated with templates is selected at 609. For example, advertisements showing large gatherings of people may be selected for individuals having high extroversion levels. Advertisements having a large number of simultaneous visual elements may be selected for individuals having the capability to process a larger number of simultaneous visual elements. At 611, stimulus material targeted to the neurological profile of the user is presented to the user.

According to various embodiments, various mechanisms such as the data collection mechanisms, the intra-modality synthesis mechanisms, cross-modality synthesis mechanisms, etc. are implemented on multiple devices. However, it is also possible that the various mechanisms be implemented in hardware, firmware, and/or software in a single system.

FIG. 7 provides one example of a system that can be used to implement one or more mechanisms. For example, the system shown in FIG. 7 may be used to implement an alternate media system.

According to particular example embodiments, a system 700 suitable for implementing particular embodiments of the present invention includes a processor 701, a memory 703, an interface 711, and a bus 715 (e.g., a PCI bus). When acting under the control of appropriate software or firmware, the processor 701 is responsible for such tasks such as pattern generation. Various specially configured devices can also be used in place of a processor 701 or in addition to processor 701. The complete implementation can also be done in custom hardware. The interface 711 is typically configured to send and receive data packets or data segments over a network. Particular examples of interfaces the device supports include host bus adapter (HBA) interfaces, Ethernet interfaces, frame relay interfaces, cable interfaces, DSL interfaces, token ring interfaces, and the like.

According to particular example embodiments, the system 700 uses memory 703 to store data, algorithms and program instructions. The program instructions may control the operation of an operating system and/or one or more applications, for example. The memory or memories may also be configured to store received data and process received data.

Because such information and program instructions may be employed to implement the systems/methods described herein, the present invention relates to tangible, machine readable media that include program instructions, state information, etc. for performing various operations described herein. Examples of machine-readable media include, but are not limited to, magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROM disks and DVDs; magneto-optical media such as optical disks; and hardware devices that are specially configured to store and perform program instructions, such as read-only memory devices (ROM) and random access memory (RAM). Examples of program instructions include both machine code, such as produced by a compiler, and files containing higher level code that may be executed by the computer using an interpreter.

Although the foregoing invention has been described in some detail for purposes of clarity of understanding, it will be apparent that certain changes and modifications may be practiced within the scope of the appended claims. Therefore, the present embodiments are to be considered as illustrative and not restrictive and the invention is not to be limited to the details given herein, but may be modified within the scope and equivalents of the appended claims. 

1020. (canceled)
 21. A system for creating media content based on a visual processing capability of a user, the system comprising: a sensor to obtain first neuro-response data from the user during exposure of the user to first media including a first number of simultaneous visual elements and second neuro-response data during exposure of the user to a second media including a second number of simultaneous visual elements, the first number different than the second number; memory including instructions; and a processor to execute the instructions to: determine a number of visual elements in a stimulus to invoke a user response in the user based on the first neuro-response data and the second neuro-response data; assign a simultaneous visual element processing capability to the user based on the determination; modify source media content to have the number of visual elements corresponding to the simultaneous visual element processing capability of the user to generate first modified media content; and output the first modified media content for exposure to the user.
 22. The system of claim 21, wherein the processor is to: determine a first attention level of the user based on the first neuro-response data; determine a second attention level of the user based on the second neuro-response data; and determine the number of visual elements in the stimulus to invoke the user response based on the first attention level and the second attention level.
 23. The system of claim 21, wherein the processor is to: identify first neural activity in the first neuro-response data; detect an absence of the first neural activity in the second neuro-response data; and determine the number of visual elements in the stimulus to invoke the user response based on the absence of the first neural activity in the second neuro-response data.
 24. The system of claim 23, wherein the sensor includes an electrode and the first neuro-response data includes electroencephalographic data, the processor to identify the first neural activity based on an interaction of a first frequency band of the electroencephalographic data and a second frequency band of the electroencephalographic data.
 25. The system of claim 21, wherein the processor is to generate a neurological profile for the user including the simultaneous visual element processing capability for the user.
 26. The system of claim 25, wherein the processor is to: determine a detail processing level for the user based on the neurological profile; and modify the source media content based on the detail processing level to generate the first modified media content.
 27. The system of claim 25, wherein the neurological profile is to further include one or more of demographic data or age data for the user, the processor to modify the source media content based on the one or more of the demographic data or the age data to generate the first modified media content.
 28. The system of claim 21, wherein the processor is to: access user purchase activity data; and modify the source media content based on the user purchase activity data to generate the first modified media content.
 29. The system of claim 21, wherein the user is a first user, the user response is a first user response, the number of visual elements is a first number of visual elements, and the simultaneous visual element processing capability is a first simultaneous visual element processing capability, and the processor is to: determine a second number of visual elements in the stimulus to invoke a second user response in a second user, the second number of visual elements different than the first number of visual elements; assign a second simultaneous visual element processing capability to the second user based on the determination, the second simultaneous visual element processing capability different than the first simultaneous visual element processing capability; and modify the source media content to have the second number of visual elements corresponding to the second simultaneous visual element processing capability of the second user to generate second modified media content, the second modified media content different than the first modified media content.
 30. The system of claim 29, wherein the processor is to: determine a detail processing level for the second user; and modify the source media content based on the detail processing level for the second user to generate the second modified media content.
 31. A tangible machine readable storage disk or storage device comprising instructions that, when executed, cause at least one machine to at least: determine a number of visual elements in a stimulus to invoke a user response in a user based on first neuro-response data obtained from the user during exposure of the user to first media including a first number of simultaneous visual elements and second neuro-response data obtained from the user during exposure of the user to a second media including a second number of simultaneous visual elements, the first number different from the second number; assign a simultaneous visual element processing capability to the user based on the determination; modify source media content to have the number of visual elements corresponding to the simultaneous visual element processing capability of the user to generate first modified media content; and output the first modified media content for exposure to the user.
 32. The storage device or storage disk of claim 31, wherein instructions, when executed, cause the at least one machine to: determine a first attention level of the user based on the first neuro-response data; determine a second attention level of the user based on the second neuro-response data; and determine the number of visual elements in the stimulus to invoke the user response based on the first attention level and the second attention level.
 33. The storage device or storage disk of claim 31, wherein instructions, when executed, cause the at least one machine to: identify first neural activity in the first neuro-response data; detect an absence of the first neural activity in the second neuro-response data; and determine the number of visual elements in the stimulus to invoke the user response based on the absence of the first neural activity in the second neuro-response data.
 34. The storage device or storage disk of claim 33, wherein the first neuro-response data includes electroencephalographic data and the instructions, when executed, cause the at least one machine to identify the first neural activity based on an interaction of a first frequency band of the electroencephalographic data and a second frequency band of the electroencephalographic data.
 35. The storage device or storage disk of claim 31, wherein the instructions, when executed, cause the at least one machine to generate a neurological profile for the user including the simultaneous visual element processing capability for the user.
 36. The storage device or storage disk of claim 35, wherein the instructions, when executed, cause the at least one machine: determine a detail processing level for the user based on the neurological profile; and modify the source media content based on the detail processing level to generate the first modified media content.
 37. The storage device or storage disk of claim 35, wherein the neurological profile is to further include one or more of demographic data or age data for the user, and wherein instructions, when executed, cause the at least one machine to modify the source media content based on the one or more of the demographic data or the age data to generate the first modified media content.
 38. The storage device or storage disk of claim 31, wherein instructions, when executed, cause the at least one machine to: access user purchase activity data; and modify the source media content based on the user purchase activity data generate the first modified media content.
 39. The storage device or storage disk of claim 31, wherein the user is a first user, the user response is a first user response, the number of visual elements is a first number of visual elements, and the simultaneous visual element processing capability is a first simultaneous visual element processing capability, and instructions, when executed, cause the at least one machine to: determine a second number of visual elements in the stimulus to invoke a second user response in a second user, the second number of visual elements different than the first number of visual elements; assign a second simultaneous visual element processing capability to the second user based on the determination, the second simultaneous visual element processing capability different than the first simultaneous visual element processing capability; and modify the source media content to have the second number of visual elements corresponding to the second simultaneous visual element processing capability of the second user to generate second modified media content, the second modified media content different than the first modified media content.
 40. The storage device or storage disk of claim 39, wherein instructions, when executed, cause the at least one machine to: determine a detail processing level for the second user; and modify the source media content based on the detail processing level for the second user to generate the second modified media content. 